//! 批处理执行模块
//!
//! 实现向量化执行和批处理优化

use super::*;
use crate::storage::tuple::{DataPageManager, Tuple};

/// 执行批次
/// 包含一批元组，用于向量化执行
#[derive(Debug, Clone)]
pub struct ExecutionBatch {
    /// 批次中的元组
    pub tuples: Vec<ExecutionTuple>,
    /// 批次模式
    pub schema: ExecutionSchema,
    /// 批次大小
    pub size: usize,
}

/// 批处理算子特征
/// 支持向量化执行的算子接口
pub trait BatchOperator: Send + Sync {
    /// 打开批处理算子
    fn open_batch(&mut self, context: &mut ExecutionContext) -> Result<()>;
    
    /// 获取下一批元组
    fn next_batch(&mut self, context: &mut ExecutionContext) -> Result<Option<ExecutionBatch>>;
    
    /// 关闭批处理算子
    fn close_batch(&mut self, context: &mut ExecutionContext) -> Result<()>;
    
    /// 获取算子的输出模式
    fn batch_schema(&self) -> &ExecutionSchema;
    
    /// 重置算子状态
    fn reset_batch(&mut self) -> Result<()>;
}

/// 批处理表扫描算子
#[derive(Debug)]
pub struct BatchTableScanOperator {
    /// 表名
    table_name: String,
    /// 输出模式
    schema: ExecutionSchema,
    /// 批次大小
    batch_size: usize,
    /// 当前页面ID
    current_page_id: Option<u64>,
    /// 当前槽位ID
    current_slot_id: u16,
    /// 数据页管理器
    page_manager: Option<DataPageManager>,
    /// 统计信息
    statistics: OperatorStatistics,
    /// 是否已打开
    is_open: bool,
}

/// 批处理过滤算子
pub struct BatchFilterOperator {
    /// 输入算子
    input: Box<dyn BatchOperator>,
    /// 过滤谓词
    predicate: FilterPredicate,
    /// 输出模式
    schema: ExecutionSchema,
    /// 批次大小
    batch_size: usize,
    /// 统计信息
    statistics: OperatorStatistics,
    /// 是否已打开
    is_open: bool,
}

/// 批处理投影算子
pub struct BatchProjectionOperator {
    /// 输入算子
    input: Box<dyn BatchOperator>,
    /// 投影列索引
    projection_indices: Vec<usize>,
    /// 输出模式
    schema: ExecutionSchema,
    /// 批次大小
    batch_size: usize,
    /// 统计信息
    statistics: OperatorStatistics,
    /// 是否已打开
    is_open: bool,
}

impl ExecutionBatch {
    /// 创建新的执行批次
    pub fn new(tuples: Vec<ExecutionTuple>, schema: ExecutionSchema) -> Self {
        let size = tuples.len();
        Self {
            tuples,
            schema,
            size,
        }
    }
    
    /// 创建空批次
    pub fn empty(schema: ExecutionSchema) -> Self {
        Self {
            tuples: Vec::new(),
            schema,
            size: 0,
        }
    }
    
    /// 检查批次是否为空
    pub fn is_empty(&self) -> bool {
        self.tuples.is_empty()
    }
    
    /// 获取批次大小
    pub fn len(&self) -> usize {
        self.tuples.len()
    }
    
    /// 添加元组到批次
    pub fn add_tuple(&mut self, tuple: ExecutionTuple) {
        self.tuples.push(tuple);
        self.size = self.tuples.len();
    }
    
    /// 过滤批次
    pub fn filter<F>(&self, predicate: F) -> ExecutionBatch
    where
        F: Fn(&ExecutionTuple) -> bool,
    {
        let filtered_tuples: Vec<ExecutionTuple> = self.tuples
            .iter()
            .filter(|tuple| predicate(tuple))
            .cloned()
            .collect();
        
        ExecutionBatch::new(filtered_tuples, self.schema.clone())
    }
    
    /// 投影批次
    pub fn project(&self, column_indices: &[usize]) -> Result<ExecutionBatch> {
        let projected_schema = self.schema.project(column_indices)?;
        let mut projected_tuples = Vec::new();
        
        for tuple in &self.tuples {
            let mut projected_values = Vec::new();
            for &index in column_indices {
                projected_values.push(tuple.get_value(index)?.clone());
            }
            
            projected_tuples.push(ExecutionTuple {
                values: projected_values,
                row_id: tuple.row_id,
                version_info: tuple.version_info.clone(),
            });
        }
        
        Ok(ExecutionBatch::new(projected_tuples, projected_schema))
    }
    
    /// 分割批次
    pub fn split(&self, chunk_size: usize) -> Vec<ExecutionBatch> {
        let mut batches = Vec::new();
        
        for chunk in self.tuples.chunks(chunk_size) {
            batches.push(ExecutionBatch::new(chunk.to_vec(), self.schema.clone()));
        }
        
        batches
    }
    
    /// 合并批次
    pub fn merge(batches: Vec<ExecutionBatch>) -> Result<ExecutionBatch> {
        if batches.is_empty() {
            return Err(Error::query_execution("无法合并空批次列表".to_string()));
        }
        
        let schema = batches[0].schema.clone();
        let mut all_tuples = Vec::new();
        
        for batch in batches {
            all_tuples.extend(batch.tuples);
        }
        
        Ok(ExecutionBatch::new(all_tuples, schema))
    }
    
    /// 计算批次内存使用量
    pub fn memory_usage(&self) -> usize {
        // 简化估算：每个元组64字节
        self.tuples.len() * 64
    }
}

impl BatchTableScanOperator {
    /// 创建新的批处理表扫描算子
    pub fn new(table_name: String, schema: ExecutionSchema, batch_size: usize) -> Self {
        Self {
            table_name,
            schema,
            batch_size,
            current_page_id: None,
            current_slot_id: 0,
            page_manager: None,
            statistics: OperatorStatistics::default(),
            is_open: false,
        }
    }
}

impl BatchOperator for BatchTableScanOperator {
    fn open_batch(&mut self, context: &mut ExecutionContext) -> Result<()> {
        if self.is_open {
            return Ok(());
        }
        
        // 获取表元数据
        let table_metadata = context.get_table_metadata(&self.table_name)
            .ok_or_else(|| Error::query_execution(format!("表 {} 不存在", self.table_name)))?;
        
        self.current_page_id = table_metadata.root_page_id;
        self.current_slot_id = 0;
        self.page_manager = Some(DataPageManager::new());
        self.is_open = true;
        
        tracing::debug!("批处理表扫描算子已打开: {}", self.table_name);
        Ok(())
    }
    
    fn next_batch(&mut self, context: &mut ExecutionContext) -> Result<Option<ExecutionBatch>> {
        if !self.is_open {
            return Err(Error::query_execution("算子未打开".to_string()));
        }
        
        let mut batch_tuples = Vec::new();
        
        // 收集一批元组
        while batch_tuples.len() < self.batch_size {
            // 如果没有页面，返回当前批次
            let page_id = match self.current_page_id {
                Some(id) => id,
                None => break,
            };
            
            // 读取当前页面
            let page = context.page_manager.read_page(page_id)?;
            let page_manager = self.page_manager.as_ref().unwrap();
            
            // 尝试读取当前槽位的元组
            let page_id = self.current_page_id.unwrap_or(0); // 简化处理
            match page_manager.read_tuple(page_id, self.current_slot_id, &page) {
                Ok(Some(tuple)) => {
                    // 检查元组可见性
                    if tuple.is_visible_to_transaction(context.transaction_id) {
                        // 转换为执行元组
                        let execution_tuple = self.convert_tuple_to_execution_tuple(&tuple)?;
                        batch_tuples.push(execution_tuple);
                    }
                    
                    // 移动到下一个槽位
                    self.current_slot_id += 1;
                    self.statistics.tuples_processed += 1;
                }
                Ok(None) => {
                    // 槽位为空，移动到下一个槽位
                    self.current_slot_id += 1;
                }
                Err(_) => {
                    // 当前页面没有更多元组，移动到下一个页面
                    // 简化实现：假设只有一个页面
                    self.current_page_id = None;
                    break;
                }
            }
        }
        
        if batch_tuples.is_empty() {
            Ok(None)
        } else {
            self.statistics.tuples_output += batch_tuples.len() as u64;
            Ok(Some(ExecutionBatch::new(batch_tuples, self.schema.clone())))
        }
    }
    
    fn close_batch(&mut self, _context: &mut ExecutionContext) -> Result<()> {
        self.is_open = false;
        self.page_manager = None;
        tracing::debug!("批处理表扫描算子已关闭: {}", self.table_name);
        Ok(())
    }
    
    fn batch_schema(&self) -> &ExecutionSchema {
        &self.schema
    }
    
    fn reset_batch(&mut self) -> Result<()> {
        self.current_page_id = None;
        self.current_slot_id = 0;
        self.statistics = OperatorStatistics::default();
        self.is_open = false;
        Ok(())
    }
}

impl BatchTableScanOperator {
    /// 将存储元组转换为执行元组
    fn convert_tuple_to_execution_tuple(&self, tuple: &Tuple) -> Result<ExecutionTuple> {
        // 简化实现：假设元组数据是序列化的Value
        let mut values = Vec::new();
        
        for i in 0..self.schema.column_count() {
            if tuple.is_null(i)? {
                values.push(Value::Null);
            } else {
                // 简化：假设所有非NULL值都是字符串
                values.push(Value::Text(format!("column_{}_data", i)));
            }
        }
        
        let version_info = VersionInfo {
            xmin: tuple.header.xmin,
            xmax: if tuple.header.xmax == 0 { None } else { Some(tuple.header.xmax) },
            committed: true,
        };
        
        Ok(ExecutionTuple::with_version(values, version_info))
    }
}

impl BatchFilterOperator {
    /// 创建新的批处理过滤算子
    pub fn new(
        input: Box<dyn BatchOperator>,
        predicate: FilterPredicate,
        batch_size: usize,
    ) -> Self {
        let schema = input.batch_schema().clone();
        
        Self {
            input,
            predicate,
            schema,
            batch_size,
            statistics: OperatorStatistics::default(),
            is_open: false,
        }
    }
}

impl BatchOperator for BatchFilterOperator {
    fn open_batch(&mut self, context: &mut ExecutionContext) -> Result<()> {
        if self.is_open {
            return Ok(());
        }
        
        self.input.open_batch(context)?;
        self.is_open = true;
        
        tracing::debug!("批处理过滤算子已打开");
        Ok(())
    }
    
    fn next_batch(&mut self, context: &mut ExecutionContext) -> Result<Option<ExecutionBatch>> {
        if !self.is_open {
            return Err(Error::query_execution("算子未打开".to_string()));
        }
        
        if let Some(input_batch) = self.input.next_batch(context)? {
            let mut filtered_tuples = Vec::new();
            
            for tuple in input_batch.tuples {
                self.statistics.tuples_processed += 1;
                
                // 评估谓词
                if self.evaluate_predicate(&tuple, &self.predicate)? {
                    filtered_tuples.push(tuple);
                }
            }
            
            self.statistics.tuples_output += filtered_tuples.len() as u64;
            
            if filtered_tuples.is_empty() {
                // 如果过滤后没有元组，尝试获取下一批
                self.next_batch(context)
            } else {
                Ok(Some(ExecutionBatch::new(filtered_tuples, self.schema.clone())))
            }
        } else {
            Ok(None)
        }
    }
    
    fn close_batch(&mut self, context: &mut ExecutionContext) -> Result<()> {
        self.input.close_batch(context)?;
        self.is_open = false;
        tracing::debug!("批处理过滤算子已关闭");
        Ok(())
    }
    
    fn batch_schema(&self) -> &ExecutionSchema {
        &self.schema
    }
    
    fn reset_batch(&mut self) -> Result<()> {
        self.input.reset_batch()?;
        self.statistics = OperatorStatistics::default();
        self.is_open = false;
        Ok(())
    }
}

impl BatchFilterOperator {
    /// 评估过滤谓词
    fn evaluate_predicate(&self, tuple: &ExecutionTuple, predicate: &FilterPredicate) -> Result<bool> {
        // 复用FilterOperator的实现
        match predicate {
            FilterPredicate::Comparison { left_column, operator, right_value } => {
                let left_value = tuple.get_value(*left_column)?;
                self.compare_values(left_value, operator, right_value)
            }
            FilterPredicate::ColumnComparison { left_column, operator, right_column } => {
                let left_value = tuple.get_value(*left_column)?;
                let right_value = tuple.get_value(*right_column)?;
                self.compare_values(left_value, operator, right_value)
            }
            FilterPredicate::And(left, right) => {
                Ok(self.evaluate_predicate(tuple, left)? && self.evaluate_predicate(tuple, right)?)
            }
            FilterPredicate::Or(left, right) => {
                Ok(self.evaluate_predicate(tuple, left)? || self.evaluate_predicate(tuple, right)?)
            }
            FilterPredicate::Not(inner) => {
                Ok(!self.evaluate_predicate(tuple, inner)?)
            }
        }
    }
    
    /// 比较两个值
    fn compare_values(&self, left: &Value, operator: &ComparisonOperator, right: &Value) -> Result<bool> {
        // 复用FilterOperator的实现
        use std::cmp::Ordering;
        
        match (left, right) {
            (Value::Null, Value::Null) => {
                Ok(matches!(operator, ComparisonOperator::Equal))
            }
            (Value::Null, _) | (_, Value::Null) => Ok(false),
            _ => {
                let comparison = match (left, right) {
                    (Value::Integer(a), Value::Integer(b)) => a.cmp(b),
                    (Value::Real(a), Value::Real(b)) => a.partial_cmp(b).unwrap_or(Ordering::Equal),
                    (Value::Text(a), Value::Text(b)) => a.cmp(b),
                    (Value::Boolean(a), Value::Boolean(b)) => a.cmp(b),
                    _ => return Err(Error::query_execution("类型不匹配的比较".to_string())),
                };
                
                let result = match operator {
                    ComparisonOperator::Equal => comparison == Ordering::Equal,
                    ComparisonOperator::NotEqual => comparison != Ordering::Equal,
                    ComparisonOperator::LessThan => comparison == Ordering::Less,
                    ComparisonOperator::LessThanOrEqual => comparison != Ordering::Greater,
                    ComparisonOperator::GreaterThan => comparison == Ordering::Greater,
                    ComparisonOperator::GreaterThanOrEqual => comparison != Ordering::Less,
                    ComparisonOperator::Like => {
                        if let (Value::Text(text), Value::Text(pattern)) = (left, right) {
                            if pattern.contains('%') {
                                let pattern_without_wildcard = pattern.replace('%', "");
                                text.contains(&pattern_without_wildcard)
                            } else {
                                text == pattern
                            }
                        } else {
                            false
                        }
                    }
                    ComparisonOperator::In => false, // TODO: 实现IN操作符
                };
                
                Ok(result)
            }
        }
    }
}
